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The project develops methods to use acoustic data for the identification of animals in the wild and in controlled settings. It is part of a broader effort to build AI-enabled methods to support
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for monitoring and controlling the brain with medical devices and imaging brain activity in new and important ways. Required knowledge Statistical signal processing, Statistical Inference, Machine learning, Deep
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, Lianli, Li, Yuan-Fang. Difficulty-controllable Multi-hop Question Generation From Knowledge Graphs. 18th International Semantic Web Conference (ISWC'19), Springer.
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of the control of the model owners. They can be easily stolen or abused if not properly protected. A recent empirical study [1] has demonstrated that half of on-device ML models are stored in plaintext form
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legal and security implications for a federated infrastructure. Similarly, this project should develop principles and mechanisms for governance, audit, and quality control of the data - including
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goals without any central control in the presence of ever changing environmental conditions and internal colony demands. The project investigates the mechanisms of self-organised task allocation in